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Learning Theory

5,334 papers

Papers per year

17
66
123
466
307
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Papers

PAC learning of Probabilistic Automaton based on the Method of Moments ICML 2016
PAC Lower Bounds and Efficient Algorithms for The Max K-Armed Bandit Problem ICML 2016
Anytime Exploration for Multi-armed Bandits using Confidence Information ICML 2016
L1-regularized Neural Networks are Improperly Learnable in Polynomial Time ICML 2016
Train faster, generalize better: Stability of stochastic gradient descent ICML 2016
A ranking approach to global optimization ICML 2016
Anytime optimal algorithms in stochastic multi-armed bandits ICML 2016
An optimal algorithm for the Thresholding Bandit Problem ICML 2016
Why Most Decisions Are Easy in Tetris—And Perhaps in Other Sequential Decision Problems, As Well ICML 2016
Barron and Cover’s Theory in Supervised Learning and its Application to Lasso ICML 2016
On the Power and Limits of Distance-Based Learning ICML 2016
Generalization Properties and Implicit Regularization for Multiple Passes SGM ICML 2016
Generalization and Exploration via Randomized Value Functions ICML 2016
Sparse Nonlinear Regression: Parameter Estimation under Nonconvexity ICML 2016
Pricing a Low-regret Seller ICML 2016
Group Equivariant Convolutional Networks ICML 2016
Multiscale Dictionary Learning: Non-Asymptotic Bounds and Robustness JMLR 2016
Convex Calibration Dimension for Multiclass Loss Matrices JMLR 2016
A Closer Look at Adaptive Regret JMLR 2016
Learning Using Anti-Training with Sacrificial Data JMLR 2016
Statistical-Computational Tradeoffs in Planted Problems and Submatrix Localization with a Growing Number of Clusters and Submatrices JMLR 2016
The Optimal Sample Complexity of PAC Learning JMLR 2016
On the Characterization of a Class of Fisher-Consistent Loss Functions and its Application to Boosting JMLR 2016
An Emphatic Approach to the Problem of Off-policy Temporal-Difference Learning JMLR 2016
Iterative Regularization for Learning with Convex Loss Functions JMLR 2016